Electronic messaging devices, referred to as “massagers”, are used to send and receive messages between users and their contacts. Many cellular phones include messagers that send and receive SMS messages. Due to their compact sizes, messagers often have limited key pads with relatively few small keys. As such, multiple key presses are often required to input a single character of text. For example, to input the character “b”, a user may be required to press on a “2” key twice. Multiple key presses for single character input is a cumbersome process, and composing a 10-20 word message may take several minutes.
Predictive text technology was integrated within messagers in order to accelerate message composition. Using such technology, one or more text predictions are presented to a user, and the user may thereby input entire words by a single key press. For example, if a user has entered characters r-e-a, text predictions may include such words as “reach”, “react”, “read”, “ready”, “real”, “realize” and “really”. A single key press enables the user to select one of these words. Moreover, even if the user wants to input a different word then those predicted, it often saves time to select one of the predicted words that is close to the user's intended word, and to modify the text accordingly. Thus, if the user wants to input the word “realign”, it is more efficient for him to select the predicted word “realize”, and then backspace twice to delete the z-e and enter the characters g-n.
Prior art text prediction technology includes “dictionary based” and “non-dictionary based” prediction. Dictionary based prediction bases its prediction upon a dictionary of common words. Products that include dictionary based prediction include T9® developed by Tegic Communications of Seattle, Wash., iTap® developed by Motorola, Inc. of Schaumburg, Ill., eZiText® developed by Zi Corporation of Calgary, AB, and Adaptx™ developed by Keypoint Technologies, Ltd. of Glasgow, Scotland. The T9 text prediction technology is described in U.S. Pat. No. 6,011,554 to King et al.
Non-dictionary based prediction bases its prediction upon statistical information for a specific language. Products that include non-dictionary based prediction include LetterWise and Wordwise developed by Eatoni Ergonomics of New York, N.Y.